A) Field of the Invention
This invention relates to a digital signal processing apparatus, and more in detail, a digital signal processing apparatus that executes a noise reduction of a digital image signal by using a wavelet transformation.
B) Description of the Related Art
FIG. 4 to FIG. 6 are schematic views for explaining a two-dimensional wavelet transformation of a digital image signal. FIG. 4 is a block diagram showing an outline of a wavelet transformation unit. FIG. 5 is a block diagram showing an outline of an inverse wavelet transformation unit. FIG. 6 is a plan view schematically showing an image signal to which the wavelet transformation is executed.
When a digital image signal X0 is input to the wavelet transformation unit 11, it is transferred to a low path filter LPF and a high path filter HPF. Each of a high-frequency-filtered (a low frequency component) signal filtered by the low path filter LPF and a low-frequency-filtered (a high frequency component) signal filtered by the high path filter HPF is transferred to a down-sampling unit 4 and a half of signals in a horizontal direction is culled to be frequency-decomposed to the sub-band data of the low frequency component in the horizontal direction L and the high frequency component in the horizontal direction H.
The low frequency component in the horizontal direction L is transferred to the low path filter LPF and the high path filter HPF. After that, each of them is transferred to the down-sampling unit 4 and is culled to a half in the vertical direction to be decomposed into sub-band data of a component LL1 consisting of low frequency components in the horizontal and vertical directions and a component LH1 consisting of a low frequency component in the horizontal direction and a high frequency component in the vertical direction. Also, the high frequency component in the horizontal direction H is transferred to the low path filter LPF and the high path filter HPF. After that, each of them is transferred to the down-sampling unit 4 and is culled to a half in the vertical direction to be decomposed into sub-band data of a component HH1 consisting of high frequency components in the horizontal and vertical directions and a component HL1 consisting of a high frequency component in the horizontal direction and a low frequency component in the vertical direction. Each of the decomposed sub-band data (LL1, LH1, HH1, HL1) is rearranged by an interleave transformation unit 5 to be arranged as a screen 100b shown in the upper right section in FIG. 6.
In the wavelet transformation unit 1, a reflexive transform can be executed to a desired sub-band data. For example, sub-band data (LL2, LH2, HH2 and HL2) shown in the lower right section in FIG. 6 can be obtained by re-inputting the horizontal and vertical low frequency component LL1 as an input signal X0 to the wavelet transformation unit 1. As described in the above, sun-band data in a specific frequency band can be obtained by repeating the reflexive transform by predetermined times to a predetermined sub-band data.
The wavelet inverse transform unit 2 recovers the decomposed sub-band data by executing the inverse transform, and the interleave inverse transform unit 5 reconstructs the recovered data to the original image.
FIG. 7 is a block diagram for explaining a noise reduction process according to a conventional digital signal processing apparatus 200 used the wavelet transformation.
The digital signal processing apparatus 200 decomposes a digital image signal X0 to the sub-band data LL1, LH1, HH1 and HL1 by the wavelet transformation already explained with reference to FIG. 4 to FIG. 6. Moreover, the sub-band data LL of low frequency components in the horizontal and vertical directions is further processed by the wavelet transformation, and transformation of the obtained sub-band data LL of low frequency components in the horizontal and vertical directions is repeated for predetermined (n) times (for example, two to eight times) to obtain sub-band data LLn, LHn, HHn and HLn. A coring process described later is executed to the obtained sub-band data LHn, HHn and HLn, and the original image signal is recovered by repeating the inverse wavelet transformations. By executing these processes, for example, low band noise can be restrained as in Japanese Laid-Open Patent 2003-134352. Besides, in this specification, further executing the wavelet transformation to the sub-band data obtained by the wavelet transformation is called “a reflexive wavelet transformation”.
FIG. 8A and FIG. 8B and FIG. 9A to FIG. 9E are graphs for explaining the coring process.
FIG. 8A is a graph showing a relationship between an input signal and an output signal without the coring process. The coring process is, for example, a process for controlling the signal when an absolute value of the input signal is lower than the threshold value (for example, making the signal impartially “0” when the signal equals to a threshold value or less than the threshold value). When the coring process is executed to the signal with the relationship shown in FIG. 8A, the input signal lower than the threshold value is out put as “0” to get a relationship of the input signal and the output signal shown in FIG. 8B.
More in detail, the wavelet transformation is executed to the input signal X0 shown in FIG. 9B to decompose it to the low frequency component L1 shown in FIG. 9B and the high frequency component H1 shown in FIG. 9C, and the coring process is executed to the high frequency component H1. By doing that, the high frequency component H1 of which a part lower than the threshold value (a part surrounded by a dotted line) is set to “0” can be obtained. Then, a recovered signal X0′ of which the noise is reduced as shown in FIG. 9E can be obtained by executing the inverse wavelet transformation to the low frequency component L1 and a high frequency component H1′.
As the above-described conventional digital signal processing apparatus, when the reflexive wavelet transformation is repeated and the coring process to the sub-band of the specific band is executed in order to reduce the specific band noise, ringing is generated on the image based on the recovered signal, and an amplitude phase may be changed. Also, to reduce the noise in the specific band, a gap of the phase will be accumulated.